Advanced technologies allow manufacturers to create products which connect the physical world to a digital world. Recent examples in the toy and game industries use radio frequency identification/near field communication (RFID/NFC) chips inside toy figures to allow recognition of these figures by an RFID sensor which is connected to the toy or game platform in order to trigger digital content in a toy or game experience. RFID is a reliable but expensive technology that requires adding costs to the figures and also requires an RFID reader to be used.
A different approach can save the costs of adding RFID chips to figures and at the same time allow the toy or game platform to include users with a mobile device such as a smartphone or tablet that lacks an RFID reader. This approach may use a built-in camera in these devices for recognition, for example of a toy figure, based on computer vision and image processing algorithms.
Such algorithms for three dimensional (3D) object recognition are well known and are mostly based on feature extraction, for example comparing extracted features to a database of features. The database may have been created by applying a learning phase on several captured images of the object to be recognized from different angles and perspectives.
A logical problem then arises which can create huge losses for manufacturers of such 3D figures, as a recognition algorithm based on a captured image cannot differentiate between a genuine 3D object and a printed or displayed image of such object. Users of such games can trick the game by showing an image on a screen or a printed image instead of the real 3D figure.